Paper Info
Title
On the application of massively parallel SIMD tree machines to certain intermediate-level vision tasks
Abstract
In this paper, we examine the implementation of two middle-level image understanding tasks on fine-grained tree-structured SIMD machines, which have highly efficient VLSI implementations. We first present one such massively parallel machine called NON-VON, and summarize the cost/performance trade-offs of such machines for vision taks. We follow with a more detailed description of the NON-VON architecture (a prototype of which has been operational since January 1985), and of the high-level parallel language in which our algorithms have been written and simulated. The heart of the paper consists of the description and analysis of algorithms for a representative Hough transform, and of an algorithm for the interpretation of moving light displays. Novel algorithmic techniques are motivated and described, and simulation timings are presented and discussed. We conclude that it is possible to exploit the available massive parallelism while avoiding many of the communication bottlenecks common at this level of image understanding, by carefully and inexpensively duplicating data and/or control information, and by delaying or avoiding the reporting of intermediate results.
Year
DOI
Venue
1986
10.1016/S0734-189X(86)80029-9
Computer Vision, Graphics and Image Processing
Keywords
Field
DocType
simd tree machine,certain intermediate-level vision task,computer science
Computer vision,Architecture,Parallel language,Massively parallel,Computer science,Parallel computing,Analysis of algorithms,Hough transform,SIMD,Exploit,High-level programming language,Artificial intelligence
Journal
Volume
Issue
ISSN
36
1
Computer Vision, Graphics and Image Processing
Citations 
PageRank 
References 
13
1.79
9
Authors
3
Name
Order
Citations
PageRank
Hussein A H Ibrahim13810.92
John R. Kender2627138.04
David Elliot Shaw3890139.33